Investigating Heat Risk Messaging Using Social Media Studies and a Survey Experiment

Extreme heat causes hundreds of deaths each year in the United States even though cost-effective protective measures are available. Heat warning messages sent by government agencies have the potential to reduce the negative impacts by motivating people to take protective actions. To help reach the potential, this dissertation examined the content of warning messages and public responses to warning messages in the US. This research analyzed three kinds of data: 1) heat warning messages posted on Twitter, 2) public comments on heat warning messages posted on Facebook, and 3) experimental results collected using an online survey. Results show that, for heat warning messages posted on Twitter, most messages mentioned temperatures and/or Heat Index. Half of messages mentioned heat-safety tips. Less than one-third of messages mentioned heat-health impacts and people’s vulnerability (who is at risk and/or which behavior is at risk). For these four types of mentions, heat warning messages that mentioned more types were retweeted more frequently. In addition, compared to listing specific vulnerable subgroups such as older adults, a statement that “anyone can be at risk” appears to be more effective in making heat warning messages personally relevant to the public. The research also shows that Facebook comments on heat warning messages can suggest people’s needs for risk messaging. The findings can inform researchers and practitioners of how to better communicate risks in the context of extreme heat and other natural hazards

Stochastic P-bifurcation in a tri-stable Van der Pol system with fractional derivative under Gaussian white noise

In this paper, we study the tri-stable stochastic P-bifurcation problem of a generalized Van der Pol system with fractional derivative under Gaussian white noise excitation. Firstly, using the principle for minimal mean square error, we show that the fractional derivative term is equivalent to a linear combination of the damping force and restoring force, so that the original system can be transformed into an equivalent integer order system. Secondly, we obtain the stationary Probability Density Function (PDF) of the system’s amplitude by the stochastic averaging, and using the singularity theory, we find the critical parametric conditions for stochastic P-bifurcation of amplitude of the system, which can make the system switch among the three steady states. Finally, we analyze different types of the stationary PDF curves of the system amplitude qualitatively by choosing parameters corresponding to each region divided by the transition set curves, and the system response can be maintained at the small amplitude near the equilibrium by selecting the appropriate unfolding parameters. We verify the theoretical analysis and calculation of the transition set by showing the consistency of the numerical results obtained by Monte Carlo simulation with the analytical results. The method used in this paper directly guides the design of the fractional order controller to adjust the response of the system

Block-Randomized Gradient Descent Methods with Importance Sampling for CP Tensor Decomposition

This work considers the problem of computing the CANDECOMP/PARAFAC (CP) decomposition of large tensors. One popular way is to translate the problem into a sequence of overdetermined least squares subproblems with Khatri-Rao product (KRP) structure. In this work, for tensor with different levels of importance in each fiber, combining stochastic optimization with randomized sampling, we present a mini-batch stochastic gradient descent algorithm with importance sampling for those special least squares subproblems. Four different sampling strategies are provided. They can avoid forming the full KRP or corresponding probabilities and sample the desired fibers from the original tensor directly. Moreover, a more practical algorithm with adaptive step size is also given. For the proposed algorithms, we present their convergence properties and numerical performance. The results on synthetic data show that our algorithms outperform the existing algorithms in terms of accuracy or the number of iterations

フレマを適切な単語カウント単位として採用したMcLeanの根拠についての一考察

本稿は，第二言語（L2）語彙研究の分野における重要なギャップ，すなわち第二言語（L2）学習者が単語の屈折形や派生形を理解する能力を扱ったMcLean（2018）の論文を検証するものである。彼の研究において，McLean は，ワードファミリーを適切なカウント単位として用いるべきとする研究に於ける結論に疑問を投げかけている。日本人EFL 学習者（N=279）を3 つの習熟度グループ（初級，中級，上級）に分け，屈折形と派生形の知識を英日翻訳テストにより測定した。その結果，全レベルの学習者において，12単語について，基本形，屈折形，派生形を理解する能力に差があることがわかった。McLean は，単語の基本形と関連する屈折形であるフレマが，ワードファミリーよりも適切な単語カウント単位であると結論付けている。 本稿では，まず主要な用語と概念について説明し，次にMcLean の論文の概要を述べる。その後，McLean の主張の妥当性を検証し，L2 語彙研究分野での重要性を評価するために，この研究の長所と短所を評価した上で，この論文の批評を行う。最後に，L2教室における形態論の扱いを含む，この研究の教育的示唆について考察する。This review article examines a paper by McLean (2018) in which he addresses an important gap in the field of second language (L2) vocabulary research: the ability of L2 learners to understand the inflected and derived forms of words. In his study, McLean questions the inferences made in research that uses the word family as an appropriate unit of counting. Japanese EFL learners (N=279) were divided into three proficiency groups (beginner, intermediate, and advanced), and their knowledge of inflectional and derivational forms was measured using an English to Japanese translation test. It was found that learners at all levels differed in their ability to understand the base form, inflected forms, and derived forms of 12 words. McLean concludes that the flemma, a word’s base form and associated inflectional forms, is therefore a more appropriate word counting unit than the word family. Our review begins with an explanation of the key terms and concepts in this field of research, followed by an overview of McLean’s paper. A critique of the paper follows in which we examine the validity of McLean’s argument, and evaluate the strengths and weaknesses of the study with a view to assessing its importance in the L2 vocabulary research field. We close with a consideration of the pedagogical implications of the study, including the treatment of morphology in the L2 classroom

Block-Randomized Stochastic Methods for Tensor Ring Decomposition

Tensor ring (TR) decomposition is a simple but effective tensor network for analyzing and interpreting latent patterns of tensors. In this work, we propose a doubly randomized optimization framework for computing TR decomposition. It can be regarded as a sensible mix of randomized block coordinate descent and stochastic gradient descent, and hence functions in a double-random manner and can achieve lightweight updates and a small memory footprint. Further, to improve the convergence, especially for ill-conditioned problems, we propose a scaled version of the framework that can be viewed as an adaptive preconditioned or diagonally-scaled variant. Four different probability distributions for selecting the mini-batch and the adaptive strategy for determining the step size are also provided. Finally, we present the theoretical properties and numerical performance for our proposals

Fully Nonlinear Numerical Simulations of Wave Interactions with Multiple Structures at Resonance

A two-dimensional boundary element method (BEM) based on potential flow theory is adopted to study the wave interactions with multiple structures at resonance. Here resonance refers to the wave resonance which appears in the gaps between structures. The wave-structure interactions problems are simulated using a mixed Euler-Lagrangian scheme, with fully nonlinear boundary conditions applied on the instantaneous free surface and wetted body surface. The numerical scheme is verified through the simulations of wave interactions with a single body. Results show that both the free surface elevation and the hydrodynamic forces can be calculated accurately enough. The first primary study proposes a numerical approach to calculate the dominant natural frequencies in the gap based on the understanding of free liquid sloshing in a tank. The effectiveness of this approach is verified through the ‘response amplitude operator’ (RAO) analysis in terms of the gap free surface elevation. The natural frequencies are found for twin barges, with various gap widths and draughts. The effects of resonance on wave forces and elevations are also analysed. The second primary study considers the resonance induced by forced heave, sway and roll of body motion at various amplitudes. Particularly, second-order resonance, which is due to the sum or difference frequency, is found especially significant when the gap width over draught ratio is large. Second-order resonance can sometimes be as pronounced as, or even stronger than, classical first-order resonance. The third primary study concerns the wave resonance induced by nonlinear regular incident waves. For hydrodynamic interactions when the two bodies are both fixed, the free surface elevations are captured, particularly the standing wave trains formed in front of the upwave structure and sheltering effect behind the leeside structure. The nonlinearity associated with incident wave steepness is taken into consideration. Then second-order resonance in the gap caused by incident waves is studied. Finally, the wave resonance behaviour in the gap when the two bodies are freely floating under incident waves is analysed

Examining the Supply Chain Management Models for Agricultural Products Under the Context of E-Commerce

Agricultural products market changes constantly along with the thriving of e-commerce and agricultural products e-commerce keeps growing as an innovative industry; however, there are still many loopholes in the management of the supply chain from beginning to end. In order to effectively address these issues, this paper utilizes the dynamic requirement forecasting method based on SVM (support vector machine) to identify and fit the secular trend in and potential cyclical fluctuation factors for the market requirements for agricultural products. The supply chain coordination decision center is established by integrating the collaborative supply management component and other components. XML technology and CORBA technology are adopted to construct the integrated management model of agricultural products supply chain in e-commerce environment. For its relatively high management level, the model established can promote both agricultural consumption and agricultural economic output, strengthen the competitiveness of enterprises in agricultural products market and realize maximization of profit targets

Design of a magnetostrictive sensor for structural health monitoring of non-ferromagnetic plates

In this work, a magnetostrictive sensor (MsS) is designed and tested for monitoring damage in a non-ferromagnetic plate. Firstly, the mechanism of the MsS to generate and detect guided shear horizontal (SH) waves in a non-ferromagnetic plate is described. Both theoretical and experimental studies are conducted in order to prove that the sensor can generate the first non-dispersive shear horizontal wave mode (SH0) suitable for monitoring of the structural health. The sensor encompasses a nickel strip, a pair of permanent magnets, C-shaped cores wound by a figure-of-eight coil. The incident wave emitted from the MsS propagates in the plate and is reflected from the plate boundaries. Since the time of the arrival can be determined from the reflected wave signal through signal processing, the velocity of the wave can be extracted. Comparing the calculated velocity with the velocity predicted by the theory, the mode of the wave can be identified with a priori knowledge of plate velocity. To demonstrate the effectiveness of the proposed sensor for structural health monitoring, the location of the damage in an aluminum plate is examined. Finally, optimum design of the sensor is determined using ANSYS program yielding improved sensor performance. The effectiveness of the optimized magnetostrictive sensor is confirmed by experimental results